Two of our LIDA Data Science Interns have just presented their latest work.
Robert Clay presented an update on the Understanding and Quantifying Uncertainty in Agent-Based Models for Smart City Forecasts project that discusses the use of an Unscented Kalman Filter to try to incorporate real-time data into a crowding model. Download Slides (pptx).
Benjamin Wilson presented his latest work on using a probabilistic programming library (Pyro) to create an agent-based model. Download Slides (pptx).